As an alternative to purchasing merchandise in person at a physical store, shoppers often remotely place orders for merchandise to be delivered. Customers may place such remote orders by a variety of means, such as by making a telephone call to a merchant or interacting with a merchant's web site.
An order generally identifies one or more items and specifies delivery information that is used to ship one or more shipments containing the ordered items. Each shipment is typically delivered from a distribution center or warehouse. To fulfill shipments, employees working at the warehouse manually retrieve items from storage locations within the warehouse, such as particular bins or shelves. This process is sometimes referred to as “picking,” the employees performing the picking may be referred to as “pickers,” and the retrieval items may be referred to as “picked items.” In large distribution centers or warehouses, picked items are often placed in totes and may be conveyed (e.g., on conveyor belts) to a sorting station that collects the items needed for each shipment.
Distribution centers and warehouses can be quite large and may rely on a substantial workforce of pickers to fulfill orders in a timely way. In distribution centers containing a large number of items, items may be stored using distinct bins or storage locations. Keeping track of such bins or locations may be a complex process. While some distribution centers may use spatially-oriented maps to show points of interest in the warehouse relative to each other, such maps are difficult to create, use, and maintain, especially when portraying a large number of uniquely identifiable locations. For example, the warehouse may need to hire industrial engineers to come in and design the initial map. These engineers may then need to revisit the warehouse periodically to update the map as the warehouse changes.
More generally, prior techniques for mapping warehouses do not effectively handle situations with a large number of items in locations that can frequently change, nor do they handle variations and changes to locations in an automated manner. Prior techniques also fail to address changes within the warehouse, such as changes in the layout and use of the warehouse, including structural changes. Examples of changes in warehouse use might include safety-related changes (e.g., a prohibition on taking a certain dangerous path between two locations), maintenance- or construction-related changes (e.g., closing/reopening a stairway), and changes provided by new transportation opportunities (e.g., faster or more maneuverable vehicles). Thus, it would be beneficial to provide automated techniques for determining information about relative locations in a warehouse, particularly in environments where locations and relationships in the warehouse change over time.